system

Abstract

Provide a system. 【Solution means】 Means for inputting tourist destination information, Means for obtaining information on admission fees and transportation costs for each tourist destination based on the tourist destination information, Means for calculating an optimal route, Means for estimating a total cost based on the optimal route, Means for displaying the optimal route and the estimated total cost to the user, Means for pre-purchasing tickets for tourist destinations, Means for visually guiding tourist destination information to the user using augmented reality technology, A system including the above.

Description

Technical Field

[0004] , , , ,

[0005] , , , ,

[0001] The technology of the present disclosure relates to a system.

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] When traveling, it is difficult for users to accurately grasp in advance the expenses required for sightseeing at the destination, and it also takes a lot of time and effort to plan an efficient way to tour the tourist destination. There is a need for a system that solves this problem and enables users to plan their trips with confidence and enjoy the local experience to the maximum extent.

Means for Solving the Problems

[0005] This invention is a system that combines means for users to input information about tourist destinations they wish to visit, means for obtaining costs related to the tourist destinations and their transportation, means for calculating the optimal itinerary, means for estimating the total cost, and means for presenting this information to the user. This system also integrates a function for purchasing tickets to tourist destinations in advance, enabling users to complete all necessary information and arrangements before their trip.

[0006] "Tourist information" refers to information such as the name, location, and characteristics of tourist spots that users wish to visit.

[0007] An "admission fee" is the charge required to enter a tourist attraction.

[0008] "Transportation expenses" refer to the costs incurred when traveling from one point to another.

[0009] An "optimal route" is a calculated path for visiting tourist attractions that minimizes travel time, distance, or cost.

[0010] "Total cost" refers to the total amount including all transportation costs to the destination and entrance fees.

[0011] A "user" is an individual or group that uses the system to plan a trip.

[0012] "Advance purchase" refers to the act of obtaining tickets for a tourist attraction before the day of travel.

[0013] A "system" is a collection of devices and software that include a series of processes and technologies that provide services to users by coordinating and operating the aforementioned means. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2]It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Embodiments for Carrying Out the Invention

[0015] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0020] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), etc.

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] The system according to the present invention encompasses the entire process, from inputting tourist destination information necessary for travel planning, to creating an efficient travel plan based on that information, and presenting it to the user.

[0036] First, the user uses their device to input information about the tourist destination they wish to visit. The device sends this input data to the server, which then retrieves the necessary data from external databases or APIs based on the received information.

[0037] The server collects information such as entrance fees and geographical coordinates for tourist attractions, as well as transportation methods and associated costs between each attraction, and uses this information to calculate the optimal route. In doing so, it employs an algorithm that incorporates factors such as minimizing travel time, distance, and cost to create a plan that most closely matches the user's preferences.

[0038] Next, the server sends the calculated route and its total cost to the user's terminal, where the user can review the proposed plan. Additionally, if the user wishes, a function is available to purchase entrance tickets to tourist attractions in advance, with the server's agent handling the online ticket purchase process.

[0039] As a concrete example, if a user wants to visit a "museum," "park," and "zoo" in a certain area, the user enters these tourist destinations into their device. The server uses this information to obtain ticket prices and transportation information for each tourist destination and creates a plan that constitutes the shortest route. The user checks this suggestion on their device, and if the suggestion is appropriate, they can purchase tickets in advance, saving time and effort on-site and allowing them to enjoy their trip. In this way, the present invention provides an environment in which users can plan their trips effectively and efficiently.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] The user uses a device to input information about the tourist destination they wish to visit. The device then sends this input data to the server.

[0043] Step 2:

[0044] Based on tourist destination information received from terminals, the server retrieves detailed information such as admission fees, location, and opening hours for each tourist destination via external databases or APIs.

[0045] Step 3:

[0046] The server also collects data on transportation methods between tourist destinations, obtaining the cost and duration of each trip. This process includes information on transportation schedules and prices.

[0047] Step 4:

[0048] Based on the data collected by the server, the optimal sightseeing route is calculated. This calculation uses a shortest path algorithm to minimize travel time and derive an efficient route that matches the user's preferences.

[0049] Step 5:

[0050] The server uses the calculation results to total all transportation and entrance fees, estimates the overall cost, and sends the result to the terminal.

[0051] Step 6:

[0052] If a user reviews the proposed plan on their device and wishes to purchase tickets in advance, they communicate this intention from their device to the server.

[0053] Step 7:

[0054] The server's AI agent handles the online booking and purchase process for tickets to various tourist destinations and retrieves confirmation information for the purchase.

[0055] Step 8:

[0056] After the server completes all reservations and purchases, it sends confirmation information to the user's device, notifying them that they are ready to travel.

[0057] (Example 1)

[0058] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0059] In modern society, efficiently planning travel routes between tourist destinations and minimizing costs is a crucial challenge for many travelers. Existing methods require significant time and effort to gather detailed information about individual tourist spots and create optimal travel plans. Furthermore, while there is a demand to purchase entrance tickets in advance to reduce hassle at the destination, there is a lack of a system that centrally manages this entire process.

[0060] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0061] In this invention, the server includes an information processing device for inputting tourist destination information, an information processing device for acquiring information on entrance fees and means of transportation for each tourist destination, and an information processing device for analyzing the collected information and calculating the optimal route considering travel distance and cost. This allows travelers to efficiently create travel plans and minimize travel routes and total costs between tourist destinations. In addition, they can purchase entrance tickets in advance and simplify procedures at the destinations.

[0062] An "information processing device for inputting tourist destination information" is an electronic device that allows users to input the name and details of a tourist destination they wish to visit, and then processes that information.

[0063] An "information processing device for acquiring information" is an electronic device that has the function of acquiring data from an external database or service based on specified conditions.

[0064] "Admission fee" refers to the fee required to enter a tourist attraction or facility.

[0065] "Means of transportation" refers to the means of transport or method used to move from one point to another.

[0066] A "route calculation information processing device" is a device that calculates the optimal route when visiting multiple locations.

[0067] "Total cost" refers to the sum of all costs incurred based on the travel route.

[0068] An "admission ticket" is a ticket that serves as proof of permission to enter a specific tourist destination or facility.

[0069] An "information processing system" refers to an entire system in which multiple information processing devices work together to perform a specific task.

[0070] This invention is an information processing system that efficiently manages tourist destination information necessary for users to plan their trips and provides optimal travel routes. Specific embodiments are described below.

[0071] The user uses a terminal to input information about the tourist destination they wish to visit. This terminal is equipped with a user interface that allows the user to input detailed information such as the name of the tourist destination and the desired date and time of visit. The terminal uses a communication module to send this information to the server.

[0072] The server retrieves necessary data from external databases and APIs based on the tourist destination information it receives. For example, it uses common map APIs and travel information APIs to collect information on the geographical coordinates of tourist destinations, admission fees, and transportation options. Data analysis tools such as Robust Data Processing Software (RDP software) are used for this process.

[0073] The server then uses the collected information to calculate the optimal travel route. This is done using an algorithm that takes various factors, including travel time and cost. For example, Dijkstra's algorithm or genetic algorithms can be used for route optimization. As a result, the proposed route is provided to the user.

[0074] For example, if a user wants to visit a "museum," "central park," and "animal sanctuary," they enter these into their terminal. The server calculates the shortest and most cost-effective route based on the location information, admission fees, and public transportation data for each facility, and presents it to the user along with the total cost. The user can review this suggestion and purchase admission tickets in advance if necessary.

[0075] An example of a prompt when using a generative AI model is, "Calculate the most efficient route between the tourist destinations specified by the user and provide detailed instructions on how to minimize costs." This allows the generative AI model to provide a predicted travel plan.

[0076] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0077] Step 1:

[0078] The user uses a terminal to input information about their travel destination. This information includes the name of the tourist spot, the desired date of visit, and any special requests (e.g., budget constraints or specific transportation preferences). The terminal prepares to send this information as input data to the server and waits until the send button is pressed.

[0079] Step 2:

[0080] The terminal sends tourist destination information received from the user to the server. The transmission method uses a common internet communication protocol (e.g., HTTP POST request). The transmitted data arrives at the server in a structured format (e.g., JSON format), and upon receiving this data, the server begins the next processing step.

[0081] Step 3:

[0082] The server analyzes the received tourist destination data and initiates a process to retrieve necessary information from external APIs and databases. Specifically, it uses a map service API to obtain geographical coordinates and travel information services to retrieve information on admission fees and transportation options. The input is the user's tourist destination data, and the output is the expanded tourist destination data.

[0083] Step 4:

[0084] The server takes expanded tourist destination data as input and applies algorithms to create the optimal travel plan, taking into account travel time and distance. Here, Dijkstra's algorithm and genetic algorithms are used to calculate the shortest path. The calculation results show the order in which to visit each tourist destination and the corresponding means of transportation and time.

[0085] Step 5:

[0086] The server calculates the optimal travel plan and estimated total cost, and sends the results to the terminal. The output is formatted for user review and ready to be displayed on the terminal. The travel plan includes the order of visits to each tourist spot, estimated travel time, entrance fees at each location, and total fares.

[0087] Step 6:

[0088] The user reviews the travel plan displayed on their device and considers whether the suggested transportation and costs meet their requirements. If the user wishes to purchase tickets in advance, they select this option on their device. This action is sent back to the server as an advance purchase request. The server receives this request, processes the online ticket purchase on their behalf, and sends purchase confirmation information to the user.

[0089] (Application Example 1)

[0090] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0091] Modern travel planning involves many time-consuming steps, such as gathering information on tourist destinations, formulating optimal travel plans, and purchasing tickets in advance. Furthermore, there are limited means of obtaining detailed, real-time visual information about destinations. As a result, this can reduce the efficiency and satisfaction of travel. The problem this invention aims to solve is to address these issues while enabling travelers to have a more efficient and satisfying experience.

[0092] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0093] In this invention, the server includes means for inputting tourist destination information, means for obtaining information on entrance fees and transportation costs for each tourist destination, means for calculating the optimal route, and means for visually guiding the user through tourist destination information using augmented reality technology. This enables travelers to simultaneously enjoy efficient travel planning and real-time visual guidance.

[0094] "Means for inputting tourist destination information" refers to a mechanism that allows users to input information about tourist destinations they wish to visit into the system via a terminal.

[0095] "Means for obtaining information on admission fees and transportation costs for each tourist destination" refers to a mechanism that retrieves admission fees and transportation costs corresponding to tourist destinations entered by the user from an external database or API.

[0096] "Means for calculating the optimal route" refers to a mechanism that uses an algorithm to calculate the optimal order of visits to maximize travel efficiency, based on acquired tourist destination information and cost information.

[0097] A "means for estimating overall costs" is a mechanism that calculates the total cost of a trip based on the optimal route.

[0098] "Means for displaying the optimal route and estimated total cost to the user" refers to a mechanism that displays the calculated optimal route and total cost on the screen of the user's terminal.

[0099] "Methods for purchasing tickets to tourist destinations in advance" refers to a system that allows users to purchase admission tickets to their chosen tourist destinations online in advance.

[0100] "A means of visually guiding users with tourist destination information using augmented reality technology" refers to a mechanism that uses augmented reality (AR) technology to overlay information about tourist destinations onto real-world scenery and provide it to users.

[0101] The following describes embodiments for carrying out the invention.

[0102] This system is designed to operate by combining the user's terminal, server, and external databases and APIs. First, the user uses a smartphone or smart glasses to input information about the tourist destinations they wish to visit into the terminal. The terminal sends this information to the server. Based on the received tourist destination information, the server retrieves entrance fees and transportation costs for each destination from external databases and APIs. The server then uses this information to calculate the optimal route for visiting the destinations.

[0103] The calculations utilize distance calculations using the Geopy library and route determination techniques based on optimization algorithms. The server sends the calculated optimal route and estimated total cost to the user's device for display. At this time, augmented reality (AR) technology is used to visually guide the user with information about tourist destinations. Specifically, by overlaying information onto images of tourist destinations on the device, users can experience detailed information realistically on the spot.

[0104] Furthermore, if the user agrees, the server can purchase entrance tickets to tourist attractions online in advance. This simplifies procedures during travel and ensures a stress-free travel experience.

[0105] For example, if a user enters that they want to visit "historical buildings, nature parks, and aquariums," the server will calculate the entrance fees, shortest routes, and travel time to these locations and suggest the optimal plan.

[0106] Using a generative AI model, prompt messages related to a tourist destination specified by the user can be generated as follows:

[0107] "This app allows users to input the tourist destinations they wish to visit (e.g., historical buildings, nature parks, aquariums), calculates and presents the optimal route, and provides real-time information about those destinations."

[0108] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0109] Step 1:

[0110] Users input information about the tourist destinations they wish to visit using a terminal. This input includes the name of the tourist destination and the desired visit date, and this data is sent to the server. The terminal allows for easy information input through its interface.

[0111] Step 2:

[0112] The server receives tourist destination information sent by users and retrieves admission fees and transportation costs for each destination. This involves using external databases and APIs to search for basic information about the tourist destinations and obtain the necessary fee data. In this step, calculations are performed to filter the retrieved data using the basic information of the tourist destination as the key.

[0113] Step 3:

[0114] The server executes a mechanism to calculate the optimal visiting route based on the acquired information. Here, the Geopy library is used to calculate the distance between each tourist spot, and the route is determined by an optimization algorithm that takes travel time into account. The input is distance data between tourist spots, and the output is the optimal visiting order.

[0115] Step 4:

[0116] The server estimates the optimal route and overall cost, and sends this information to the user's terminal. This information is displayed on the user's terminal, allowing them to visually confirm their travel plan. The display is optimized for user layout, presenting the information in an easy-to-read format.

[0117] Step 5:

[0118] If the user agrees, the server will initiate the process of purchasing admission tickets to the tourist attraction online in advance. This step involves integration with the e-commerce system, and once the user's purchase intention is confirmed, the payment process will proceed.

[0119] Step 6:

[0120] The user's device processes the data necessary to visually guide them through tourist information using augmented reality (AR) technology and displays it on the screen. Input is the optimal visiting route and tourist information, and output is the information displayed via AR. AR data is displayed in real time through the device's camera.

[0121] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0122] The system according to the present invention includes not only basic functions to support travel planning, but also a function to recognize the user's emotions and dynamically adjust the plan based on them. This system handles a series of processes from inputting information about tourist destinations to presenting travel plans and purchasing tickets in advance, and incorporates feedback from an emotion engine.

[0123] The process begins with the user entering the tourist destinations they wish to visit into the system via their device, and this information is sent to the server. Based on the information received, the server obtains information from external sources to calculate entrance fees, transportation costs, and the optimal route for each tourist destination. The server analyzes this information to create an optimal tour plan and estimate the overall cost.

[0124] The emotion engine analyzes the user's emotional state through user input and interaction. This analysis is used by the server to customize travel suggestions. For example, if the user is feeling stressed, it prioritizes relaxing destinations and suggests routes with minimal travel burden. Furthermore, if the user's emotions change, a newly optimized plan is restructured and presented.

[0125] As a concrete example, suppose a user inputs their plans to visit an art museum, a botanical garden, and a theme park into the system, and is then presented with an optimal travel plan. If the user expresses feelings of joy through their device during the trip, the emotion engine can recognize this and suggest extending the time spent at the theme park to maximize the experience. In this way, the system dynamically adjusts the plan according to the user's emotions, playing a role in improving the quality of the trip.

[0126] The following describes the processing flow.

[0127] Step 1:

[0128] The user uses a device to input information about the tourist destination they wish to visit. The device then sends this input data to the server.

[0129] Step 2:

[0130] Based on the tourist destination information received by the terminal, the server retrieves information about admission fees, locations, and opening hours for each tourist destination from external databases and APIs.

[0131] Step 3:

[0132] The server also collects data on transportation methods between tourist destinations, obtaining the cost and duration of each trip. This process includes transportation schedules and fare information.

[0133] Step 4:

[0134] The server calculates the optimal sightseeing route based on the information it collects. It considers various factors such as travel time, distance, and cost minimization to derive the most efficient route for the user.

[0135] Step 5:

[0136] The server calculates the route and total cost, sends it to the terminal, and proposes it to the user. The user then confirms it on the terminal.

[0137] Step 6:

[0138] The emotion engine analyzes the user's emotional state through their interactions. Data used includes touch patterns, input speed, and facial expression recognition.

[0139] Step 7:

[0140] The server receives the results of the emotion engine's analysis and adjusts the selection of sightseeing routes and facilities according to the user's current emotions. This adjustment provides a plan that better suits the user's preferences and current mood.

[0141] Step 8:

[0142] The user reviews the proposal, and if emotional modifications are needed, they make another request to the server from their device. The server then reconfigures the plan based on that request.

[0143] Step 9:

[0144] Upon user consent, an agent on the server pre-purchases tickets for tourist attractions online. This process involves verifying payment information and retrieving ticket information.

[0145] Step 10:

[0146] The server sends final confirmation information to the device, letting the user know that they are ready to travel. This allows the user to prepare to start their trip as planned.

[0147] (Example 2)

[0148] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0149] In modern tourism planning, traditional systems operate based on pre-set plans, making it difficult to respond immediately to users' changing emotions and preferences. Furthermore, they fail to consider user emotions in their planning, resulting in a lack of optimal travel quality.

[0150] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0151] In this invention, the server includes means for inputting tourist destination information, means for acquiring information based on the tourist destination information, and means for analyzing the user's emotional state and dynamically adjusting travel suggestions. This makes it possible to provide flexible and personalized travel plans that respond to the user's emotions.

[0152] "Tourist information" refers to data about the region or facility that travelers plan to visit, including details related to specific places, events, or activities.

[0153] A "route" refers to a travel route that outlines a series of visiting sequences to efficiently tour multiple tourist destinations.

[0154] "Emotional state" refers to the user's direct reactions and feedback to the travel plan, as well as the psychological state they experience while using the system.

[0155] "Dynamic adjustment" refers to the process of changing and optimizing travel plans and sightseeing suggestions in real time to respond immediately to user needs and preferences.

[0156] "Optimization" is a method of efficiently structuring each element of a travel plan in order to maximize user satisfaction and convenience.

[0157] The system for implementing this invention has a function to support travel planning and has the characteristic of dynamically adjusting the plan based on the user's emotional state. First, the user uses a terminal to input the tourist destinations they wish to visit. The terminal has a function to receive the user's input and send it to the server. For example, the user inputs tourist destinations such as "art museum," "botanical garden," and "theme park," and the system plans the trip based on this.

[0158] The server uses external resources such as tourism information APIs and transportation information APIs to obtain tourist destination information. Using this data, the server calculates the optimal route and overall cost. Furthermore, the server is equipped with an emotion engine that analyzes user feedback and interactions to determine the user's emotional state. The results of the emotion analysis are used to modify the tourism recommendations. For example, if the user is feeling stressed, the server can suggest tourist spots that prioritize relaxation and plans that involve less travel.

[0159] For example, if a user inputs their emotional state via a device during their trip, the server can analyze this in real time and reconstruct and present a thoughtful travel plan. This dynamic functionality allows users to enjoy a more personalized travel experience.

[0160] The following prompt is an example of using a generative AI model.

[0161] "Currently, the tourist destinations I'd like to visit are art museums, botanical gardens, and theme parks. I want to minimize stress, so please suggest a plan that involves minimal travel."

[0162] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0163] Step 1:

[0164] This step involves the user using their device to input the tourist destination they wish to visit. The user operates a device such as a smartphone or tablet, entering the name of the tourist destination, such as "art museum," "botanical garden," or "theme park," and then submitting the input. The entered data is sent from the device to the server. The output at this stage is digital data related to the user's tourist destination selection.

[0165] Step 2:

[0166] This step involves the server receiving tourist destination information sent by the user and retrieving related information. The server accesses tourist information APIs and transportation information APIs to collect data such as admission fees, opening hours, and transportation options for each tourist destination. Specifically, API requests are issued, and real-time data is retrieved. The output contains detailed information about each tourist destination.

[0167] Step 3:

[0168] This step involves the server using collected data to calculate the optimal route and the total cost of the trip. The server processes the collected information and uses algorithms to optimize the order of visits. It also provides cost estimates. The data obtained in step 2 is used as input, and the route and cost estimate are output. Specific operations include map data analysis and distance calculations.

[0169] Step 4:

[0170] This step involves the server analyzing the user's emotional state using an emotion engine. When a user inputs their emotional state via a terminal during their trip, that information is sent to the server. The server analyzes this information, identifies the user's emotional state, and outputs it. The data used for emotion analysis includes text-input comments and responses to questions. The specific operation involves emotion analysis using natural language processing techniques.

[0171] Step 5:

[0172] This step involves the server dynamically adjusting the sightseeing recommendations based on the analysis results. The server reconstructs the sightseeing plan based on the emotional information obtained in step 4, optimizing it to match the user's emotions, such as minimizing the burden of travel. The input is the user's emotional state and the route and cost data obtained in step 3, and the output is the newly adjusted sightseeing plan.

[0173] Step 6:

[0174] This step involves the server sending the final travel plan to the terminal and displaying it to the user. The terminal displays the received plan on its user interface, allowing the user to select the next action. The output of step 5 is taken as input, and the display to the user is taken as output. Specifically, the operation involves displaying the travel plan details and selection options on the screen.

[0175] (Application Example 2)

[0176] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0177] Conventional tourism planning systems are unable to dynamically adjust plans based on the user's emotional state, making it difficult to provide users with the highest level of satisfaction. Therefore, there is a need to recognize the user's emotions in real time and flexibly optimize the plan based on that.

[0178] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0179] In this invention, the server includes means for inputting tourist destination information, means for obtaining information on admission fees and transportation costs for each tourist destination based on the tourist destination information, means for calculating the optimal route, and means for analyzing the user's emotional state and adjusting the sightseeing plan. This enables dynamic adjustment of the sightseeing plan in accordance with the user's emotions.

[0180] "Tourist destination information" refers to detailed information about a tourist destination, such as its name, location, characteristics, and the activities and events offered.

[0181] An "admission fee" is a charge paid for access to a tourist attraction or facility.

[0182] "Transportation expenses" refer to the costs incurred for the means of getting to a tourist destination.

[0183] A "route" is the optimal travel path set out when visiting multiple tourist destinations.

[0184] "Total cost" refers to the sum of all entrance fees, transportation costs, and other related expenses based on the sightseeing plan.

[0185] "Means of purchasing tickets in advance" refers to methods and devices for reserving and obtaining tickets such as admission tickets to tourist attractions or transportation passes before traveling.

[0186] "Emotional state" refers to the type and intensity of emotions a user exhibits in a particular situation.

[0187] An "emotion engine" is software or an algorithm used to analyze emotions from user behavior and input data.

[0188] The system for implementing this invention consists of a terminal, a server, and an emotion engine. The terminal provides an interface for the user to input information about tourist destinations they wish to visit and transmits the input information to the server. The server receives this information and retrieves information such as entrance fees and transportation costs for each tourist destination through external databases or APIs.

[0189] The server uses this information to calculate the optimal route and overall cost. The calculated information is returned to the terminal in a visualized format and presented to the user. The emotion engine analyzes user input and interaction data obtained through the terminal to determine the user's emotional state. Based on the user's state, such as feeling stressed or happy, the server dynamically adjusts and optimizes the proposed plan.

[0190] For example, if a user inputs the museum or theme park they plan to visit, and emotional data from their trip detects a sense of exhilaration, the server can suggest extending their stay. This process is repeated in real time, ensuring the user always has the best possible experience.

[0191] Examples of prompts for a generative AI model include: "Adjust the city sightseeing plan based on the user's emotions. Choose places to visit from museums, botanical gardens, and shopping malls."

[0192] The hardware will be a smartphone, and the software will use Python and an emotion recognition library (e.g., TENSORFLOW®). An API (e.g., TriPad® visor API) will be used to obtain tourist information.

[0193] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0194] Step 1:

[0195] The terminal provides an interface for users to input information about tourist destinations they wish to visit. This input information includes the name and category of the tourist destination and is important data based on the user's preferences. The entered tourist destination information is then transmitted from the terminal to the server.

[0196] Step 2:

[0197] Based on the received tourist destination information, the server uses an external API to retrieve information on entrance fees and transportation costs for each tourist destination. This process involves communicating with an external database, obtaining the necessary cost data, organizing the results, and passing them on to the next step.

[0198] Step 3:

[0199] The server uses the data obtained above to calculate the optimal sightseeing route. Here, it executes an algorithm to minimize the user's travel time and distance, and generates the calculated optimal route information and the total cost associated with that route.

[0200] Step 4:

[0201] The server sends the generated optimal route and estimated total cost to the user's device. The device receives this information and presents it to the user in a visualized format. The data is displayed clearly on the interface so that the user can consider what action to take next.

[0202] Step 5:

[0203] The device passes user interaction and entered emotional state data to the emotion engine. The emotion engine analyzes the user's emotional state from their facial expressions and text input and returns the determination result to the server.

[0204] Step 6:

[0205] The server adjusts the sightseeing plan as needed based on data from the emotion engine. If the user reacts positively to the presented plan, it strengthens it; if they react negatively, it flexibly suggests alternatives. The recalculated plan is then presented to the user.

[0206] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0207] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0208] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0209] [Second Embodiment]

[0210] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0211] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0212] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0213] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0214] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0215] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0216] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0217] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0218] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0219] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0220] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0221] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0222] The system according to the present invention encompasses the entire process, from inputting tourist destination information necessary for travel planning, to creating an efficient travel plan based on that information, and presenting it to the user.

[0223] First, the user uses their device to input information about the tourist destination they wish to visit. The device sends this input data to the server, which then retrieves the necessary data from external databases or APIs based on the received information.

[0224] The server collects information such as entrance fees and geographical coordinates for tourist attractions, as well as transportation methods and associated costs between each attraction, and uses this information to calculate the optimal route. In doing so, it employs an algorithm that incorporates factors such as minimizing travel time, distance, and cost to create a plan that most closely matches the user's preferences.

[0225] Next, the server sends the calculated route and its total cost to the user's terminal, where the user can review the proposed plan. Additionally, if the user wishes, a function is available to purchase entrance tickets to tourist attractions in advance, with the server's agent handling the online ticket purchase process.

[0226] As a concrete example, if a user wants to visit a "museum," "park," and "zoo" in a certain area, the user enters these tourist destinations into their device. The server uses this information to obtain ticket prices and transportation information for each tourist destination and creates a plan that constitutes the shortest route. The user checks this suggestion on their device, and if the suggestion is appropriate, they can purchase tickets in advance, saving time and effort on-site and allowing them to enjoy their trip. In this way, the present invention provides an environment in which users can plan their trips effectively and efficiently.

[0227] The following describes the processing flow.

[0228] Step 1:

[0229] The user uses a device to input information about the tourist destination they wish to visit. The device then sends this input data to the server.

[0230] Step 2:

[0231] Based on tourist destination information received from terminals, the server retrieves detailed information such as admission fees, location, and opening hours for each tourist destination via external databases or APIs.

[0232] Step 3:

[0233] The server also collects data on transportation methods between tourist destinations, obtaining the cost and duration of each trip. This process includes information on transportation schedules and prices.

[0234] Step 4:

[0235] Based on the data collected by the server, the optimal sightseeing route is calculated. This calculation uses a shortest path algorithm to minimize travel time and derive an efficient route that matches the user's preferences.

[0236] Step 5:

[0237] The server uses the calculation results to total all transportation and entrance fees, estimates the overall cost, and sends the result to the terminal.

[0238] Step 6:

[0239] If a user reviews the proposed plan on their device and wishes to purchase tickets in advance, they communicate this intention from their device to the server.

[0240] Step 7:

[0241] The server's AI agent handles the online booking and purchase process for tickets to various tourist destinations and retrieves confirmation information for the purchase.

[0242] Step 8:

[0243] After the server completes all reservations and purchases, it sends confirmation information to the user's device, notifying them that they are ready to travel.

[0244] (Example 1)

[0245] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0246] In modern society, efficiently planning travel routes between tourist destinations and minimizing costs is a crucial challenge for many travelers. Existing methods require significant time and effort to gather detailed information about individual tourist spots and create optimal travel plans. Furthermore, while there is a demand to purchase entrance tickets in advance to reduce hassle at the destination, there is a lack of a system that centrally manages this entire process.

[0247] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0248] In this invention, the server includes an information processing device for inputting tourist destination information, an information processing device for acquiring information on entrance fees and means of transportation for each tourist destination, and an information processing device for analyzing the collected information and calculating the optimal route considering travel distance and cost. This allows travelers to efficiently create travel plans and minimize travel routes and total costs between tourist destinations. In addition, they can purchase entrance tickets in advance and simplify procedures at the destinations.

[0249] An "information processing device for inputting tourist destination information" is an electronic device that allows users to input the name and details of a tourist destination they wish to visit, and then processes that information.

[0250] An "information processing device for acquiring information" is an electronic device that has the function of acquiring data from an external database or service based on specified conditions.

[0251] "Admission fee" refers to the fee required to enter a tourist attraction or facility.

[0252] "Means of transportation" refers to the means of transport or method used to move from one point to another.

[0253] A "route calculation information processing device" is a device that calculates the optimal route when visiting multiple locations.

[0254] "Total cost" refers to the sum of all costs incurred based on the travel route.

[0255] An "admission ticket" is a ticket that serves as proof of permission to enter a specific tourist destination or facility.

[0256] An "information processing system" refers to an entire system in which multiple information processing devices work together to perform a specific task.

[0257] This invention is an information processing system that efficiently manages tourist destination information necessary for users to plan their trips and provides optimal travel routes. Specific embodiments are described below.

[0258] The user uses a terminal to input information about the tourist destination they wish to visit. This terminal is equipped with a user interface that allows the user to input detailed information such as the name of the tourist destination and the desired date and time of visit. The terminal uses a communication module to send this information to the server.

[0259] The server retrieves necessary data from external databases and APIs based on the tourist destination information it receives. For example, it uses common map APIs and travel information APIs to collect information on the geographical coordinates of tourist destinations, admission fees, and transportation options. Data analysis tools such as Robust Data Processing Software (RDP software) are used for this process.

[0260] The server then uses the collected information to calculate the optimal travel route. This is done using an algorithm that takes various factors, including travel time and cost. For example, Dijkstra's algorithm or genetic algorithms can be used for route optimization. As a result, the proposed route is provided to the user.

[0261] For example, if a user wants to visit a "museum," "central park," and "animal sanctuary," they enter these into their terminal. The server calculates the shortest and most cost-effective route based on the location information, admission fees, and public transportation data for each facility, and presents it to the user along with the total cost. The user can review this suggestion and purchase admission tickets in advance if necessary.

[0262] An example of a prompt when using a generative AI model is, "Calculate the most efficient route between the tourist destinations specified by the user and provide detailed instructions on how to minimize costs." This allows the generative AI model to provide a predicted travel plan.

[0263] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0264] Step 1:

[0265] The user uses a terminal to input information about their travel destination. This information includes the name of the tourist spot, the desired date of visit, and any special requests (e.g., budget constraints or specific transportation preferences). The terminal prepares to send this information as input data to the server and waits until the send button is pressed.

[0266] Step 2:

[0267] The terminal sends tourist destination information received from the user to the server. The transmission method uses a common internet communication protocol (e.g., HTTP POST request). The transmitted data arrives at the server in a structured format (e.g., JSON format), and upon receiving this data, the server begins the next processing step.

[0268] Step 3:

[0269] The server analyzes the received tourist destination data and initiates a process to retrieve necessary information from external APIs and databases. Specifically, it uses a map service API to obtain geographical coordinates and travel information services to retrieve information on admission fees and transportation options. The input is the user's tourist destination data, and the output is the expanded tourist destination data.

[0270] Step 4:

[0271] The server takes expanded tourist destination data as input and applies algorithms to create the optimal travel plan, taking into account travel time and distance. Here, Dijkstra's algorithm and genetic algorithms are used to calculate the shortest path. The calculation results show the order in which to visit each tourist destination and the corresponding means of transportation and time.

[0272] Step 5:

[0273] The server calculates the optimal travel plan and estimated total cost, and sends the results to the terminal. The output is formatted for user review and ready to be displayed on the terminal. The travel plan includes the order of visits to each tourist spot, estimated travel time, entrance fees at each location, and total fares.

[0274] Step 6:

[0275] The user reviews the travel plan displayed on their device and considers whether the suggested transportation and costs meet their requirements. If the user wishes to purchase tickets in advance, they select this option on their device. This action is sent back to the server as an advance purchase request. The server receives this request, processes the online ticket purchase on their behalf, and sends purchase confirmation information to the user.

[0276] (Application Example 1)

[0277] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0278] Modern travel planning involves a lot of time-consuming tasks, such as gathering information about tourist destinations, formulating an optimal travel plan, and pre-purchasing tickets. In addition, there are limited means to visually obtain detailed information about the destination in real time. As a result, it may reduce the efficiency and satisfaction of travel. The problem that this invention aims to solve is to enable travelers to have a more efficient and satisfactory experience while eliminating these problems.

[0279] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0280] In this invention, the server includes means for inputting tourist destination information, means for acquiring information on admission fees and transportation costs for each tourist destination, means for calculating an optimal route, and means for visually guiding the tourist destination information to the user using augmented reality technology. As a result, travelers can simultaneously enjoy the creation of an efficient travel plan and real-time visual guidance.

[0281] The "means for inputting tourist destination information" is a mechanism for the user to input information about the tourist destination they wish to visit into the system through a terminal.

[0282] The "means for acquiring information on admission fees and transportation costs for each tourist destination" is a mechanism for acquiring admission fees and transportation costs corresponding to the tourist destination input by the user from an external database or API.

[0283] The "means for calculating an optimal route" is a mechanism for calculating, by an algorithm, the optimal visit order for maximizing the efficiency of travel based on the acquired tourist destination information and cost information.

[0284] The "means for estimating the total cost" is a mechanism for calculating the cost of the entire trip based on the optimal route.

[0285] The means for "displaying the optimal route and the estimated total cost to the user" is a mechanism for presenting the calculated optimal route and total cost on the screen of the user terminal.

[0286] The means for "pre-purchasing tickets for tourist attractions" is a mechanism for the server to pre-purchase online the admission tickets for the tourist attractions selected by the user.

[0287] The means for "visually guiding the user to tourist attraction information using augmented reality technology" is a mechanism for using augmented reality (AR) technology to overlay information about tourist attractions on the real scenery and provide it to the user.

[0288] The embodiments for implementing the invention are shown below.

[0289] This system is designed to operate by combining the user's terminal, server, external database, and API. First, the user inputs information about the tourist attractions they want to visit into the terminal using a smartphone or smart glasses. The terminal sends this information to the server. The server obtains the admission fees and transportation costs for each tourist attraction from an external database or API based on the received tourist attraction information. The server uses this information to calculate the optimal visiting route.

[0290] For the calculation, distance calculation using the Geopy library and route determination technology based on optimization algorithms are used. The server sends the calculated optimal route and the estimated total cost to the user's terminal for display. At this time, augmented reality (AR) technology is utilized to visually guide the user to tourist attraction information. Specifically, by overlaying information on the images of tourist attractions on the terminal, the user can experience detailed information realistically on-site.

[0291] Also, when the user gives consent, it is possible for the server to pre-purchase the admission tickets for tourist attractions online. This simplifies the procedures during the trip and realizes a stress-free travel experience.

[0292] For example, if a user enters that they want to visit "historical buildings, nature parks, and aquariums," the server will calculate the entrance fees, shortest routes, and travel time to these locations and suggest the optimal plan.

[0293] Using a generative AI model, prompt messages related to a tourist destination specified by the user can be generated as follows:

[0294] "This app allows users to input the tourist destinations they wish to visit (e.g., historical buildings, nature parks, aquariums), calculates and presents the optimal route, and provides real-time information about those destinations."

[0295] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0296] Step 1:

[0297] Users input information about the tourist destinations they wish to visit using a terminal. This input includes the name of the tourist destination and the desired visit date, and this data is sent to the server. The terminal allows for easy information input through its interface.

[0298] Step 2:

[0299] The server receives tourist destination information sent by users and retrieves admission fees and transportation costs for each destination. This involves using external databases and APIs to search for basic information about the tourist destinations and obtain the necessary fee data. In this step, calculations are performed to filter the retrieved data using the basic information of the tourist destination as the key.

[0300] Step 3:

[0301] The server executes a mechanism to calculate the optimal visiting route based on the acquired information. Here, the Geopy library is used to calculate the distance between each tourist spot, and the route is determined by an optimization algorithm that takes travel time into account. The input is distance data between tourist spots, and the output is the optimal visiting order.

[0302] Step 4:

[0303] The server estimates the optimal route and the total cost, and transmits that information to the user's terminal. By displaying this information on the user terminal, the user can visually confirm the travel plan. The display is optimized for the user layout and presented in an easy-to-view form.

[0304] Step 5:

[0305] When the user gives consent, the server executes the process of pre-purchasing the admission tickets for the tourist attractions online. In this step, cooperation with the e-commerce system is carried out, and once the purchase intention of the user is confirmed, the payment procedure proceeds.

[0306] Step 6:

[0307] The user's terminal processes the data necessary to visually guide the tourist attraction information using augmented reality (AR) technology and displays it on the screen. The input is the optimal visit route and tourist attraction information, and the output is the information displayed through AR. The AR data is displayed in real time through the camera of the terminal.

[0308] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform specific processing using the user's emotion.

[0309] In addition to the basic function of supporting the tourism plan, the system according to the present invention includes a function of recognizing the user's emotion and dynamically adjusting the plan based on it. This system is responsible for a series of processes from the input of tourist attraction information to the presentation of the travel plan and the pre-purchase of tickets, and incorporates feedback from the emotion engine.

[0310] The process begins with the user entering the tourist destinations they wish to visit into the system via their device, and this information is sent to the server. Based on the information received, the server obtains information from external sources to calculate entrance fees, transportation costs, and the optimal route for each tourist destination. The server analyzes this information to create an optimal tour plan and estimate the overall cost.

[0311] The emotion engine analyzes the user's emotional state through user input and interaction. This analysis is used by the server to customize travel suggestions. For example, if the user is feeling stressed, it prioritizes relaxing destinations and suggests routes with minimal travel burden. Furthermore, if the user's emotions change, a newly optimized plan is restructured and presented.

[0312] As a concrete example, suppose a user inputs their plans to visit an art museum, a botanical garden, and a theme park into the system, and is then presented with an optimal travel plan. If the user expresses feelings of joy through their device during the trip, the emotion engine can recognize this and suggest extending the time spent at the theme park to maximize the experience. In this way, the system dynamically adjusts the plan according to the user's emotions, playing a role in improving the quality of the trip.

[0313] The following describes the processing flow.

[0314] Step 1:

[0315] The user uses a device to input information about the tourist destination they wish to visit. The device then sends this input data to the server.

[0316] Step 2:

[0317] Based on the tourist destination information received by the terminal, the server retrieves information about admission fees, locations, and opening hours for each tourist destination from external databases and APIs.

[0318] Step 3:

[0319] The server also collects data on transportation methods between tourist destinations, obtaining the cost and duration of each trip. This process includes transportation schedules and fare information.

[0320] Step 4:

[0321] The server calculates the optimal sightseeing route based on the information it collects. It considers various factors such as travel time, distance, and cost minimization to derive the most efficient route for the user.

[0322] Step 5:

[0323] The server calculates the route and total cost, sends it to the terminal, and proposes it to the user. The user then confirms it on the terminal.

[0324] Step 6:

[0325] The emotion engine analyzes the user's emotional state through their interactions. Data used includes touch patterns, input speed, and facial expression recognition.

[0326] Step 7:

[0327] The server receives the results of the emotion engine's analysis and adjusts the selection of sightseeing routes and facilities according to the user's current emotions. This adjustment provides a plan that better suits the user's preferences and current mood.

[0328] Step 8:

[0329] The user reviews the proposal, and if emotional modifications are needed, they make another request to the server from their device. The server then reconfigures the plan based on that request.

[0330] Step 9:

[0331] Upon user consent, an agent on the server pre-purchases tickets for tourist attractions online. This process involves verifying payment information and retrieving ticket information.

[0332] Step 10:

[0333] The server sends final confirmation information to the device, letting the user know that they are ready to travel. This allows the user to prepare to start their trip as planned.

[0334] (Example 2)

[0335] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0336] In modern tourism planning, traditional systems operate based on pre-set plans, making it difficult to respond immediately to users' changing emotions and preferences. Furthermore, they fail to consider user emotions in their planning, resulting in a lack of optimal travel quality.

[0337] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0338] In this invention, the server includes means for inputting tourist destination information, means for acquiring information based on the tourist destination information, and means for analyzing the user's emotional state and dynamically adjusting travel suggestions. This makes it possible to provide flexible and personalized travel plans that respond to the user's emotions.

[0339] "Tourist information" refers to data about the region or facility that travelers plan to visit, including details related to specific places, events, or activities.

[0340] A "route" refers to a travel route that outlines a series of visiting sequences to efficiently tour multiple tourist destinations.

[0341] "Emotional state" refers to the user's direct reactions and feedback to the travel plan, as well as the psychological state they experience while using the system.

[0342] "Dynamic adjustment" refers to the process of changing and optimizing travel plans and sightseeing suggestions in real time to respond immediately to user needs and preferences.

[0343] "Optimization" is a method of efficiently structuring each element of a travel plan in order to maximize user satisfaction and convenience.

[0344] The system for implementing this invention has a function to support travel planning and has the characteristic of dynamically adjusting the plan based on the user's emotional state. First, the user uses a terminal to input the tourist destinations they wish to visit. The terminal has a function to receive the user's input and send it to the server. For example, the user inputs tourist destinations such as "art museum," "botanical garden," and "theme park," and the system plans the trip based on this.

[0345] The server uses external resources such as tourism information APIs and transportation information APIs to obtain tourist destination information. Using this data, the server calculates the optimal route and overall cost. Furthermore, the server is equipped with an emotion engine that analyzes user feedback and interactions to determine the user's emotional state. The results of the emotion analysis are used to modify the tourism recommendations. For example, if the user is feeling stressed, the server can suggest tourist spots that prioritize relaxation and plans that involve less travel.

[0346] For example, if a user inputs their emotional state via a device during their trip, the server can analyze this in real time and reconstruct and present a thoughtful travel plan. This dynamic functionality allows users to enjoy a more personalized travel experience.

[0347] The following prompt is an example of using a generative AI model.

[0348] "Currently, the tourist destinations I'd like to visit are art museums, botanical gardens, and theme parks. I want to minimize stress, so please suggest a plan that involves minimal travel."

[0349] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0350] Step 1:

[0351] This step involves the user using their device to input the tourist destination they wish to visit. The user operates a device such as a smartphone or tablet, entering the name of the tourist destination, such as "art museum," "botanical garden," or "theme park," and then submitting the input. The entered data is sent from the device to the server. The output at this stage is digital data related to the user's tourist destination selection.

[0352] Step 2:

[0353] This step involves the server receiving tourist destination information sent by the user and retrieving related information. The server accesses tourist information APIs and transportation information APIs to collect data such as admission fees, opening hours, and transportation options for each tourist destination. Specifically, API requests are issued, and real-time data is retrieved. The output contains detailed information about each tourist destination.

[0354] Step 3:

[0355] This step involves the server using collected data to calculate the optimal route and the total cost of the trip. The server processes the collected information and uses algorithms to optimize the order of visits. It also provides cost estimates. The data obtained in step 2 is used as input, and the route and cost estimate are output. Specific operations include map data analysis and distance calculations.

[0356] Step 4:

[0357] This step involves the server analyzing the user's emotional state using an emotion engine. When a user inputs their emotional state via a terminal during their trip, that information is sent to the server. The server analyzes this information, identifies the user's emotional state, and outputs it. The data used for emotion analysis includes text-input comments and responses to questions. The specific operation involves emotion analysis using natural language processing techniques.

[0358] Step 5:

[0359] This step involves the server dynamically adjusting the sightseeing recommendations based on the analysis results. The server reconstructs the sightseeing plan based on the emotional information obtained in step 4, optimizing it to match the user's emotions, such as minimizing the burden of travel. The input is the user's emotional state and the route and cost data obtained in step 3, and the output is the newly adjusted sightseeing plan.

[0360] Step 6:

[0361] This step involves the server sending the final travel plan to the terminal and displaying it to the user. The terminal displays the received plan on its user interface, allowing the user to select the next action. The output of step 5 is taken as input, and the display to the user is taken as output. Specifically, the operation involves displaying the travel plan details and selection options on the screen.

[0362] (Application Example 2)

[0363] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0364] Conventional tourism planning systems are unable to dynamically adjust plans based on the user's emotional state, making it difficult to provide users with the highest level of satisfaction. Therefore, there is a need to recognize the user's emotions in real time and flexibly optimize the plan based on that.

[0365] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0366] In this invention, the server includes means for inputting tourist destination information, means for obtaining information on admission fees and transportation costs for each tourist destination based on the tourist destination information, means for calculating the optimal route, and means for analyzing the user's emotional state and adjusting the sightseeing plan. This enables dynamic adjustment of the sightseeing plan in accordance with the user's emotions.

[0367] "Tourist destination information" refers to detailed information about a tourist destination, such as its name, location, characteristics, and the activities and events offered.

[0368] An "admission fee" is a charge paid for access to a tourist attraction or facility.

[0369] "Transportation expenses" refer to the costs incurred for the means of getting to a tourist destination.

[0370] A "route" is the optimal travel path set out when visiting multiple tourist destinations.

[0371] "Total cost" refers to the sum of all entrance fees, transportation costs, and other related expenses based on the sightseeing plan.

[0372] "Means of purchasing tickets in advance" refers to methods and devices for reserving and obtaining tickets such as admission tickets to tourist attractions or transportation passes before traveling.

[0373] "Emotional state" refers to the type and intensity of emotions a user exhibits in a particular situation.

[0374] An "emotion engine" is software or an algorithm used to analyze emotions from user behavior and input data.

[0375] The system for implementing this invention consists of a terminal, a server, and an emotion engine. The terminal provides an interface for the user to input information about tourist destinations they wish to visit and transmits the input information to the server. The server receives this information and retrieves information such as entrance fees and transportation costs for each tourist destination through external databases or APIs.

[0376] The server uses this information to calculate the optimal route and overall cost. The calculated information is returned to the terminal in a visualized format and presented to the user. The emotion engine analyzes user input and interaction data obtained through the terminal to determine the user's emotional state. Based on the user's state, such as feeling stressed or happy, the server dynamically adjusts and optimizes the proposed plan.

[0377] For example, if a user inputs the museum or theme park they plan to visit, and emotional data from their trip detects a sense of exhilaration, the server can suggest extending their stay. This process is repeated in real time, ensuring the user always has the best possible experience.

[0378] Examples of prompts for a generative AI model include: "Adjust the city sightseeing plan based on the user's emotions. Choose places to visit from museums, botanical gardens, and shopping malls."

[0379] The hardware will be a smartphone, and the software will use Python and an emotion recognition library (e.g., TensorFlow). An API (e.g., TripAdvisor API) will be used to obtain tourist information.

[0380] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0381] Step 1:

[0382] The terminal provides an interface for users to input information about tourist destinations they wish to visit. This input information includes the name and category of the tourist destination and is important data based on the user's preferences. The entered tourist destination information is then transmitted from the terminal to the server.

[0383] Step 2:

[0384] Based on the received tourist destination information, the server uses an external API to retrieve information on entrance fees and transportation costs for each tourist destination. This process involves communicating with an external database, obtaining the necessary cost data, organizing the results, and passing them on to the next step.

[0385] Step 3:

[0386] The server uses the data obtained above to calculate the optimal sightseeing route. Here, it executes an algorithm to minimize the user's travel time and distance, and generates the calculated optimal route information and the total cost associated with that route.

[0387] Step 4:

[0388] The server sends the generated optimal route and estimated total cost to the user's device. The device receives this information and presents it to the user in a visualized format. The data is displayed clearly on the interface so that the user can consider what action to take next.

[0389] Step 5:

[0390] The device passes user interaction and entered emotional state data to the emotion engine. The emotion engine analyzes the user's emotional state from their facial expressions and text input and returns the determination result to the server.

[0391] Step 6:

[0392] The server adjusts the sightseeing plan as needed based on data from the emotion engine. If the user reacts positively to the presented plan, it strengthens it; if they react negatively, it flexibly suggests alternatives. The recalculated plan is then presented to the user.

[0393] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0394] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0395] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0396] [Third Embodiment]

[0397] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0398] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0399] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0400] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0401] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0402] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0403] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0404] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0405] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0406] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0407] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0408] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0409] The system according to the present invention encompasses the entire process, from inputting tourist destination information necessary for travel planning, to creating an efficient travel plan based on that information, and presenting it to the user.

[0410] First, the user uses their device to input information about the tourist destination they wish to visit. The device sends this input data to the server, which then retrieves the necessary data from external databases or APIs based on the received information.

[0411] The server collects information such as entrance fees and geographical coordinates for tourist attractions, as well as transportation methods and associated costs between each attraction, and uses this information to calculate the optimal route. In doing so, it employs an algorithm that incorporates factors such as minimizing travel time, distance, and cost to create a plan that most closely matches the user's preferences.

[0412] Next, the server sends the calculated route and its total cost to the user's terminal, where the user can review the proposed plan. Additionally, if the user wishes, a function is available to purchase entrance tickets to tourist attractions in advance, with the server's agent handling the online ticket purchase process.

[0413] As a concrete example, if a user wants to visit a "museum," "park," and "zoo" in a certain area, the user enters these tourist destinations into their device. The server uses this information to obtain ticket prices and transportation information for each tourist destination and creates a plan that constitutes the shortest route. The user checks this suggestion on their device, and if the suggestion is appropriate, they can purchase tickets in advance, saving time and effort on-site and allowing them to enjoy their trip. In this way, the present invention provides an environment in which users can plan their trips effectively and efficiently.

[0414] The following describes the processing flow.

[0415] Step 1:

[0416] The user uses a device to input information about the tourist destination they wish to visit. The device then sends this input data to the server.

[0417] Step 2:

[0418] Based on tourist destination information received from terminals, the server retrieves detailed information such as admission fees, location, and opening hours for each tourist destination via external databases or APIs.

[0419] Step 3:

[0420] The server also collects data on transportation methods between tourist destinations, obtaining the cost and duration of each trip. This process includes information on transportation schedules and prices.

[0421] Step 4:

[0422] Based on the data collected by the server, the optimal sightseeing route is calculated. This calculation uses a shortest path algorithm to minimize travel time and derive an efficient route that matches the user's preferences.

[0423] Step 5:

[0424] The server uses the calculation results to total all transportation and entrance fees, estimates the overall cost, and sends the result to the terminal.

[0425] Step 6:

[0426] If a user reviews the proposed plan on their device and wishes to purchase tickets in advance, they communicate this intention from their device to the server.

[0427] Step 7:

[0428] The server's AI agent handles the online booking and purchase process for tickets to various tourist destinations and retrieves confirmation information for the purchase.

[0429] Step 8:

[0430] After the server completes all reservations and purchases, it sends confirmation information to the user's device, notifying them that they are ready to travel.

[0431] (Example 1)

[0432] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0433] In modern society, efficiently planning travel routes between tourist destinations and minimizing costs is a crucial challenge for many travelers. Existing methods require significant time and effort to gather detailed information about individual tourist spots and create optimal travel plans. Furthermore, while there is a demand to purchase entrance tickets in advance to reduce hassle at the destination, there is a lack of a system that centrally manages this entire process.

[0434] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0435] In this invention, the server includes an information processing device for inputting tourist destination information, an information processing device for acquiring information on entrance fees and means of transportation for each tourist destination, and an information processing device for analyzing the collected information and calculating the optimal route considering travel distance and cost. This allows travelers to efficiently create travel plans and minimize travel routes and total costs between tourist destinations. In addition, they can purchase entrance tickets in advance and simplify procedures at the destinations.

[0436] An "information processing device for inputting tourist destination information" is an electronic device that allows users to input the name and details of a tourist destination they wish to visit, and then processes that information.

[0437] An "information processing device for acquiring information" is an electronic device that has the function of acquiring data from an external database or service based on specified conditions.

[0438] "Admission fee" refers to the fee required to enter a tourist attraction or facility.

[0439] "Means of transportation" refers to the means of transport or method used to move from one point to another.

[0440] A "route calculation information processing device" is a device that calculates the optimal route when visiting multiple locations.

[0441] "Total cost" refers to the sum of all costs incurred based on the travel route.

[0442] An "admission ticket" is a ticket that serves as proof of permission to enter a specific tourist destination or facility.

[0443] An "information processing system" refers to an entire system in which multiple information processing devices work together to perform a specific task.

[0444] This invention is an information processing system that efficiently manages tourist destination information necessary for users to plan their trips and provides optimal travel routes. Specific embodiments are described below.

[0445] The user uses a terminal to input information about the tourist destination they wish to visit. This terminal is equipped with a user interface that allows the user to input detailed information such as the name of the tourist destination and the desired date and time of visit. The terminal uses a communication module to send this information to the server.

[0446] The server retrieves necessary data from external databases and APIs based on the tourist destination information it receives. For example, it uses common map APIs and travel information APIs to collect information on the geographical coordinates of tourist destinations, admission fees, and transportation options. Data analysis tools such as Robust Data Processing Software (RDP software) are used for this process.

[0447] The server then uses the collected information to calculate the optimal travel route. This is done using an algorithm that takes various factors, including travel time and cost. For example, Dijkstra's algorithm or genetic algorithms can be used for route optimization. As a result, the proposed route is provided to the user.

[0448] For example, if a user wants to visit a "museum," "central park," and "animal sanctuary," they enter these into their terminal. The server calculates the shortest and most cost-effective route based on the location information, admission fees, and public transportation data for each facility, and presents it to the user along with the total cost. The user can review this suggestion and purchase admission tickets in advance if necessary.

[0449] An example of a prompt when using a generative AI model is, "Calculate the most efficient route between the tourist destinations specified by the user and provide detailed instructions on how to minimize costs." This allows the generative AI model to provide a predicted travel plan.

[0450] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0451] Step 1:

[0452] The user uses a terminal to input information about their travel destination. This information includes the name of the tourist spot, the desired date of visit, and any special requests (e.g., budget constraints or specific transportation preferences). The terminal prepares to send this information as input data to the server and waits until the send button is pressed.

[0453] Step 2:

[0454] The terminal sends tourist destination information received from the user to the server. The transmission method uses a common internet communication protocol (e.g., HTTP POST request). The transmitted data arrives at the server in a structured format (e.g., JSON format), and upon receiving this data, the server begins the next processing step.

[0455] Step 3:

[0456] The server analyzes the received tourist destination data and initiates a process to retrieve necessary information from external APIs and databases. Specifically, it uses a map service API to obtain geographical coordinates and travel information services to retrieve information on admission fees and transportation options. The input is the user's tourist destination data, and the output is the expanded tourist destination data.

[0457] Step 4:

[0458] The server takes expanded tourist destination data as input and applies algorithms to create the optimal travel plan, taking into account travel time and distance. Here, Dijkstra's algorithm and genetic algorithms are used to calculate the shortest path. The calculation results show the order in which to visit each tourist destination and the corresponding means of transportation and time.

[0459] Step 5:

[0460] The server calculates the optimal travel plan and estimated total cost, and sends the results to the terminal. The output is formatted for user review and ready to be displayed on the terminal. The travel plan includes the order of visits to each tourist spot, estimated travel time, entrance fees at each location, and total fares.

[0461] Step 6:

[0462] The user reviews the travel plan displayed on their device and considers whether the suggested transportation and costs meet their requirements. If the user wishes to purchase tickets in advance, they select this option on their device. This action is sent back to the server as an advance purchase request. The server receives this request, processes the online ticket purchase on their behalf, and sends purchase confirmation information to the user.

[0463] (Application Example 1)

[0464] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0465] Modern travel planning involves many time-consuming steps, such as gathering information on tourist destinations, formulating optimal travel plans, and purchasing tickets in advance. Furthermore, there are limited means of obtaining detailed, real-time visual information about destinations. As a result, this can reduce the efficiency and satisfaction of travel. The problem this invention aims to solve is to address these issues while enabling travelers to have a more efficient and satisfying experience.

[0466] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0467] In this invention, the server includes means for inputting tourist destination information, means for obtaining information on entrance fees and transportation costs for each tourist destination, means for calculating the optimal route, and means for visually guiding the user through tourist destination information using augmented reality technology. This enables travelers to simultaneously enjoy efficient travel planning and real-time visual guidance.

[0468] "Means for inputting tourist destination information" refers to a mechanism that allows users to input information about tourist destinations they wish to visit into the system via a terminal.

[0469] "Means for obtaining information on admission fees and transportation costs for each tourist destination" refers to a mechanism that retrieves admission fees and transportation costs corresponding to tourist destinations entered by the user from an external database or API.

[0470] "Means for calculating the optimal route" refers to a mechanism that uses an algorithm to calculate the optimal order of visits to maximize travel efficiency, based on acquired tourist destination information and cost information.

[0471] A "means for estimating overall costs" is a mechanism that calculates the total cost of a trip based on the optimal route.

[0472] "Means for displaying the optimal route and estimated total cost to the user" refers to a mechanism that displays the calculated optimal route and total cost on the screen of the user's terminal.

[0473] "Methods for purchasing tickets to tourist destinations in advance" refers to a system that allows users to purchase admission tickets to their chosen tourist destinations online in advance.

[0474] "A means of visually guiding users with tourist destination information using augmented reality technology" refers to a mechanism that uses augmented reality (AR) technology to overlay information about tourist destinations onto real-world scenery and provide it to users.

[0475] The following describes embodiments for carrying out the invention.

[0476] This system is designed to operate by combining the user's terminal, server, and external databases and APIs. First, the user uses a smartphone or smart glasses to input information about the tourist destinations they wish to visit into the terminal. The terminal sends this information to the server. Based on the received tourist destination information, the server retrieves entrance fees and transportation costs for each destination from external databases and APIs. The server then uses this information to calculate the optimal route for visiting the destinations.

[0477] The calculations utilize distance calculations using the Geopy library and route determination techniques based on optimization algorithms. The server sends the calculated optimal route and estimated total cost to the user's device for display. At this time, augmented reality (AR) technology is used to visually guide the user with information about tourist destinations. Specifically, by overlaying information onto images of tourist destinations on the device, users can experience detailed information realistically on the spot.

[0478] Furthermore, if the user agrees, the server can purchase entrance tickets to tourist attractions online in advance. This simplifies procedures during travel and ensures a stress-free travel experience.

[0479] For example, if a user enters that they want to visit "historical buildings, nature parks, and aquariums," the server will calculate the entrance fees, shortest routes, and travel time to these locations and suggest the optimal plan.

[0480] Using a generative AI model, prompt messages related to a tourist destination specified by the user can be generated as follows:

[0481] "This app allows users to input the tourist destinations they wish to visit (e.g., historical buildings, nature parks, aquariums), calculates and presents the optimal route, and provides real-time information about those destinations."

[0482] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0483] Step 1:

[0484] Users input information about the tourist destinations they wish to visit using a terminal. This input includes the name of the tourist destination and the desired visit date, and this data is sent to the server. The terminal allows for easy information input through its interface.

[0485] Step 2:

[0486] The server receives tourist destination information sent by users and retrieves admission fees and transportation costs for each destination. This involves using external databases and APIs to search for basic information about the tourist destinations and obtain the necessary fee data. In this step, calculations are performed to filter the retrieved data using the basic information of the tourist destination as the key.

[0487] Step 3:

[0488] The server executes a mechanism to calculate the optimal visiting route based on the acquired information. Here, the Geopy library is used to calculate the distance between each tourist spot, and the route is determined by an optimization algorithm that takes travel time into account. The input is distance data between tourist spots, and the output is the optimal visiting order.

[0489] Step 4:

[0490] The server estimates the optimal route and overall cost, and sends this information to the user's terminal. This information is displayed on the user's terminal, allowing them to visually confirm their travel plan. The display is optimized for user layout, presenting the information in an easy-to-read format.

[0491] Step 5:

[0492] If the user agrees, the server will initiate the process of purchasing admission tickets to the tourist attraction online in advance. This step involves integration with the e-commerce system, and once the user's purchase intention is confirmed, the payment process will proceed.

[0493] Step 6:

[0494] The user's device processes the data necessary to visually guide them through tourist information using augmented reality (AR) technology and displays it on the screen. Input is the optimal visiting route and tourist information, and output is the information displayed via AR. AR data is displayed in real time through the device's camera.

[0495] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0496] The system according to the present invention includes not only basic functions to support travel planning, but also a function to recognize the user's emotions and dynamically adjust the plan based on them. This system handles a series of processes from inputting information about tourist destinations to presenting travel plans and purchasing tickets in advance, and incorporates feedback from an emotion engine.

[0497] The process begins with the user entering the tourist destinations they wish to visit into the system via their device, and this information is sent to the server. Based on the information received, the server obtains information from external sources to calculate entrance fees, transportation costs, and the optimal route for each tourist destination. The server analyzes this information to create an optimal tour plan and estimate the overall cost.

[0498] The emotion engine analyzes the user's emotional state through user input and interaction. This analysis is used by the server to customize travel suggestions. For example, if the user is feeling stressed, it prioritizes relaxing destinations and suggests routes with minimal travel burden. Furthermore, if the user's emotions change, a newly optimized plan is restructured and presented.

[0499] As a concrete example, suppose a user inputs their plans to visit an art museum, a botanical garden, and a theme park into the system, and is then presented with an optimal travel plan. If the user expresses feelings of joy through their device during the trip, the emotion engine can recognize this and suggest extending the time spent at the theme park to maximize the experience. In this way, the system dynamically adjusts the plan according to the user's emotions, playing a role in improving the quality of the trip.

[0500] The following describes the processing flow.

[0501] Step 1:

[0502] The user uses a device to input information about the tourist destination they wish to visit. The device then sends this input data to the server.

[0503] Step 2:

[0504] Based on the tourist destination information received by the terminal, the server retrieves information about admission fees, locations, and opening hours for each tourist destination from external databases and APIs.

[0505] Step 3:

[0506] The server also collects data on transportation methods between tourist destinations, obtaining the cost and duration of each trip. This process includes transportation schedules and fare information.

[0507] Step 4:

[0508] The server calculates the optimal sightseeing route based on the information it collects. It considers various factors such as travel time, distance, and cost minimization to derive the most efficient route for the user.

[0509] Step 5:

[0510] The server calculates the route and total cost, sends it to the terminal, and proposes it to the user. The user then confirms it on the terminal.

[0511] Step 6:

[0512] The emotion engine analyzes the user's emotional state through their interactions. Data used includes touch patterns, input speed, and facial expression recognition.

[0513] Step 7:

[0514] The server receives the results of the emotion engine's analysis and adjusts the selection of sightseeing routes and facilities according to the user's current emotions. This adjustment provides a plan that better suits the user's preferences and current mood.

[0515] Step 8:

[0516] The user reviews the proposal, and if emotional modifications are needed, they make another request to the server from their device. The server then reconfigures the plan based on that request.

[0517] Step 9:

[0518] Upon user consent, an agent on the server pre-purchases tickets for tourist attractions online. This process involves verifying payment information and retrieving ticket information.

[0519] Step 10:

[0520] The server sends final confirmation information to the device, letting the user know that they are ready to travel. This allows the user to prepare to start their trip as planned.

[0521] (Example 2)

[0522] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0523] In modern tourism planning, traditional systems operate based on pre-set plans, making it difficult to respond immediately to users' changing emotions and preferences. Furthermore, they fail to consider user emotions in their planning, resulting in a lack of optimal travel quality.

[0524] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0525] In this invention, the server includes means for inputting tourist destination information, means for acquiring information based on the tourist destination information, and means for analyzing the user's emotional state and dynamically adjusting travel suggestions. This makes it possible to provide flexible and personalized travel plans that respond to the user's emotions.

[0526] "Tourist information" refers to data about the region or facility that travelers plan to visit, including details related to specific places, events, or activities.

[0527] A "route" refers to a travel route that outlines a series of visiting sequences to efficiently tour multiple tourist destinations.

[0528] "Emotional state" refers to the user's direct reactions and feedback to the travel plan, as well as the psychological state they experience while using the system.

[0529] "Dynamic adjustment" refers to the process of changing and optimizing travel plans and sightseeing suggestions in real time to respond immediately to user needs and preferences.

[0530] "Optimization" is a method of efficiently structuring each element of a travel plan in order to maximize user satisfaction and convenience.

[0531] The system for implementing this invention has a function to support travel planning and has the characteristic of dynamically adjusting the plan based on the user's emotional state. First, the user uses a terminal to input the tourist destinations they wish to visit. The terminal has a function to receive the user's input and send it to the server. For example, the user inputs tourist destinations such as "art museum," "botanical garden," and "theme park," and the system plans the trip based on this.

[0532] The server uses external resources such as tourism information APIs and transportation information APIs to obtain tourist destination information. Using this data, the server calculates the optimal route and overall cost. Furthermore, the server is equipped with an emotion engine that analyzes user feedback and interactions to determine the user's emotional state. The results of the emotion analysis are used to modify the tourism recommendations. For example, if the user is feeling stressed, the server can suggest tourist spots that prioritize relaxation and plans that involve less travel.

[0533] For example, if a user inputs their emotional state via a device during their trip, the server can analyze this in real time and reconstruct and present a thoughtful travel plan. This dynamic functionality allows users to enjoy a more personalized travel experience.

[0534] The following prompt is an example of using a generative AI model.

[0535] "Currently, the tourist destinations I'd like to visit are art museums, botanical gardens, and theme parks. I want to minimize stress, so please suggest a plan that involves minimal travel."

[0536] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0537] Step 1:

[0538] This step involves the user using their device to input the tourist destination they wish to visit. The user operates a device such as a smartphone or tablet, entering the name of the tourist destination, such as "art museum," "botanical garden," or "theme park," and then submitting the input. The entered data is sent from the device to the server. The output at this stage is digital data related to the user's tourist destination selection.

[0539] Step 2:

[0540] This step involves the server receiving tourist destination information sent by the user and retrieving related information. The server accesses tourist information APIs and transportation information APIs to collect data such as admission fees, opening hours, and transportation options for each tourist destination. Specifically, API requests are issued, and real-time data is retrieved. The output contains detailed information about each tourist destination.

[0541] Step 3:

[0542] This step involves the server using collected data to calculate the optimal route and the total cost of the trip. The server processes the collected information and uses algorithms to optimize the order of visits. It also provides cost estimates. The data obtained in step 2 is used as input, and the route and cost estimate are output. Specific operations include map data analysis and distance calculations.

[0543] Step 4:

[0544] This step involves the server analyzing the user's emotional state using an emotion engine. When a user inputs their emotional state via a terminal during their trip, that information is sent to the server. The server analyzes this information, identifies the user's emotional state, and outputs it. The data used for emotion analysis includes text-input comments and responses to questions. The specific operation involves emotion analysis using natural language processing techniques.

[0545] Step 5:

[0546] This step involves the server dynamically adjusting the sightseeing recommendations based on the analysis results. The server reconstructs the sightseeing plan based on the emotional information obtained in step 4, optimizing it to match the user's emotions, such as minimizing the burden of travel. The input is the user's emotional state and the route and cost data obtained in step 3, and the output is the newly adjusted sightseeing plan.

[0547] Step 6:

[0548] This step involves the server sending the final travel plan to the terminal and displaying it to the user. The terminal displays the received plan on its user interface, allowing the user to select the next action. The output of step 5 is taken as input, and the display to the user is taken as output. Specifically, the operation involves displaying the travel plan details and selection options on the screen.

[0549] (Application Example 2)

[0550] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0551] Conventional tourism planning systems are unable to dynamically adjust plans based on the user's emotional state, making it difficult to provide users with the highest level of satisfaction. Therefore, there is a need to recognize the user's emotions in real time and flexibly optimize the plan based on that.

[0552] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0553] In this invention, the server includes means for inputting tourist destination information, means for obtaining information on admission fees and transportation costs for each tourist destination based on the tourist destination information, means for calculating the optimal route, and means for analyzing the user's emotional state and adjusting the sightseeing plan. This enables dynamic adjustment of the sightseeing plan in accordance with the user's emotions.

[0554] "Tourist destination information" refers to detailed information about a tourist destination, such as its name, location, characteristics, and the activities and events offered.

[0555] An "admission fee" is a charge paid for access to a tourist attraction or facility.

[0556] "Transportation expenses" refer to the costs incurred for the means of getting to a tourist destination.

[0557] A "route" is the optimal travel path set out when visiting multiple tourist destinations.

[0558] "Total cost" refers to the sum of all entrance fees, transportation costs, and other related expenses based on the sightseeing plan.

[0559] "Means of purchasing tickets in advance" refers to methods and devices for reserving and obtaining tickets such as admission tickets to tourist attractions or transportation passes before traveling.

[0560] "Emotional state" refers to the type and intensity of emotions a user exhibits in a particular situation.

[0561] An "emotion engine" is software or an algorithm used to analyze emotions from user behavior and input data.

[0562] The system for implementing this invention consists of a terminal, a server, and an emotion engine. The terminal provides an interface for the user to input information about tourist destinations they wish to visit and transmits the input information to the server. The server receives this information and retrieves information such as entrance fees and transportation costs for each tourist destination through external databases or APIs.

[0563] The server uses this information to calculate the optimal route and overall cost. The calculated information is returned to the terminal in a visualized format and presented to the user. The emotion engine analyzes user input and interaction data obtained through the terminal to determine the user's emotional state. Based on the user's state, such as feeling stressed or happy, the server dynamically adjusts and optimizes the proposed plan.

[0564] For example, if a user inputs the museum or theme park they plan to visit, and emotional data from their trip detects a sense of exhilaration, the server can suggest extending their stay. This process is repeated in real time, ensuring the user always has the best possible experience.

[0565] Examples of prompts for a generative AI model include: "Adjust the city sightseeing plan based on the user's emotions. Choose places to visit from museums, botanical gardens, and shopping malls."

[0566] The hardware will be a smartphone, and the software will use Python and an emotion recognition library (e.g., TensorFlow). An API (e.g., TripAdvisor API) will be used to obtain tourist information.

[0567] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0568] Step 1:

[0569] The terminal provides an interface for users to input information about tourist destinations they wish to visit. This input information includes the name and category of the tourist destination and is important data based on the user's preferences. The entered tourist destination information is then transmitted from the terminal to the server.

[0570] Step 2:

[0571] Based on the received tourist destination information, the server uses an external API to retrieve information on entrance fees and transportation costs for each tourist destination. This process involves communicating with an external database, obtaining the necessary cost data, organizing the results, and passing them on to the next step.

[0572] Step 3:

[0573] The server uses the data obtained above to calculate the optimal sightseeing route. Here, it executes an algorithm to minimize the user's travel time and distance, and generates the calculated optimal route information and the total cost associated with that route.

[0574] Step 4:

[0575] The server sends the generated optimal route and estimated total cost to the user's device. The device receives this information and presents it to the user in a visualized format. The data is displayed clearly on the interface so that the user can consider what action to take next.

[0576] Step 5:

[0577] The device passes user interaction and entered emotional state data to the emotion engine. The emotion engine analyzes the user's emotional state from their facial expressions and text input and returns the determination result to the server.

[0578] Step 6:

[0579] The server adjusts the sightseeing plan as needed based on data from the emotion engine. If the user reacts positively to the presented plan, it strengthens it; if they react negatively, it flexibly suggests alternatives. The recalculated plan is then presented to the user.

[0580] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0581] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0582] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0583] [Fourth Embodiment]

[0584] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0585] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0586] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0587] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0588] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0589] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0590] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0591] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0592] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0593] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0594] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0595] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0596] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0597] The system according to the present invention encompasses the entire process, from inputting tourist destination information necessary for travel planning, to creating an efficient travel plan based on that information, and presenting it to the user.

[0598] First, the user uses their device to input information about the tourist destination they wish to visit. The device sends this input data to the server, which then retrieves the necessary data from external databases or APIs based on the received information.

[0599] The server collects information such as entrance fees and geographical coordinates for tourist attractions, as well as transportation methods and associated costs between each attraction, and uses this information to calculate the optimal route. In doing so, it employs an algorithm that incorporates factors such as minimizing travel time, distance, and cost to create a plan that most closely matches the user's preferences.

[0600] Next, the server sends the calculated route and its total cost to the user's terminal, where the user can review the proposed plan. Additionally, if the user wishes, a function is available to purchase entrance tickets to tourist attractions in advance, with the server's agent handling the online ticket purchase process.

[0601] As a concrete example, if a user wants to visit a "museum," "park," and "zoo" in a certain area, the user enters these tourist destinations into their device. The server uses this information to obtain ticket prices and transportation information for each tourist destination and creates a plan that constitutes the shortest route. The user checks this suggestion on their device, and if the suggestion is appropriate, they can purchase tickets in advance, saving time and effort on-site and allowing them to enjoy their trip. In this way, the present invention provides an environment in which users can plan their trips effectively and efficiently.

[0602] The following describes the processing flow.

[0603] Step 1:

[0604] The user uses a device to input information about the tourist destination they wish to visit. The device then sends this input data to the server.

[0605] Step 2:

[0606] Based on tourist destination information received from terminals, the server retrieves detailed information such as admission fees, location, and opening hours for each tourist destination via external databases or APIs.

[0607] Step 3:

[0608] The server also collects data on transportation methods between tourist destinations, obtaining the cost and duration of each trip. This process includes information on transportation schedules and prices.

[0609] Step 4:

[0610] Based on the data collected by the server, the optimal sightseeing route is calculated. This calculation uses a shortest path algorithm to minimize travel time and derive an efficient route that matches the user's preferences.

[0611] Step 5:

[0612] The server uses the calculation results to total all transportation and entrance fees, estimates the overall cost, and sends the result to the terminal.

[0613] Step 6:

[0614] If a user reviews the proposed plan on their device and wishes to purchase tickets in advance, they communicate this intention from their device to the server.

[0615] Step 7:

[0616] The server's AI agent handles the online booking and purchase process for tickets to various tourist destinations and retrieves confirmation information for the purchase.

[0617] Step 8:

[0618] After the server completes all reservations and purchases, it sends confirmation information to the user's device, notifying them that they are ready to travel.

[0619] (Example 1)

[0620] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0621] In modern society, efficiently planning travel routes between tourist destinations and minimizing costs is a crucial challenge for many travelers. Existing methods require significant time and effort to gather detailed information about individual tourist spots and create optimal travel plans. Furthermore, while there is a demand to purchase entrance tickets in advance to reduce hassle at the destination, there is a lack of a system that centrally manages this entire process.

[0622] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0623] In this invention, the server includes an information processing device for inputting tourist destination information, an information processing device for acquiring information on entrance fees and means of transportation for each tourist destination, and an information processing device for analyzing the collected information and calculating the optimal route considering travel distance and cost. This allows travelers to efficiently create travel plans and minimize travel routes and total costs between tourist destinations. In addition, they can purchase entrance tickets in advance and simplify procedures at the destinations.

[0624] An "information processing device for inputting tourist destination information" is an electronic device that allows users to input the name and details of a tourist destination they wish to visit, and then processes that information.

[0625] An "information processing device for acquiring information" is an electronic device that has the function of acquiring data from an external database or service based on specified conditions.

[0626] "Admission fee" refers to the fee required to enter a tourist attraction or facility.

[0627] "Means of transportation" refers to the means of transport or method used to move from one point to another.

[0628] A "route calculation information processing device" is a device that calculates the optimal route when visiting multiple locations.

[0629] "Total cost" refers to the sum of all costs incurred based on the travel route.

[0630] An "admission ticket" is a ticket that serves as proof of permission to enter a specific tourist destination or facility.

[0631] An "information processing system" refers to an entire system in which multiple information processing devices work together to perform a specific task.

[0632] This invention is an information processing system that efficiently manages tourist destination information necessary for users to plan their trips and provides optimal travel routes. Specific embodiments are described below.

[0633] The user uses a terminal to input information about the tourist destination they wish to visit. This terminal is equipped with a user interface that allows the user to input detailed information such as the name of the tourist destination and the desired date and time of visit. The terminal uses a communication module to send this information to the server.

[0634] The server retrieves necessary data from external databases and APIs based on the tourist destination information it receives. For example, it uses common map APIs and travel information APIs to collect information on the geographical coordinates of tourist destinations, admission fees, and transportation options. Data analysis tools such as Robust Data Processing Software (RDP software) are used for this process.

[0635] The server then uses the collected information to calculate the optimal travel route. This is done using an algorithm that takes various factors, including travel time and cost. For example, Dijkstra's algorithm or genetic algorithms can be used for route optimization. As a result, the proposed route is provided to the user.

[0636] For example, if a user wants to visit a "museum," "central park," and "animal sanctuary," they enter these into their terminal. The server calculates the shortest and most cost-effective route based on the location information, admission fees, and public transportation data for each facility, and presents it to the user along with the total cost. The user can review this suggestion and purchase admission tickets in advance if necessary.

[0637] An example of a prompt when using a generative AI model is, "Calculate the most efficient route between the tourist destinations specified by the user and provide detailed instructions on how to minimize costs." This allows the generative AI model to provide a predicted travel plan.

[0638] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0639] Step 1:

[0640] The user uses a terminal to input information about their travel destination. This information includes the name of the tourist spot, the desired date of visit, and any special requests (e.g., budget constraints or specific transportation preferences). The terminal prepares to send this information as input data to the server and waits until the send button is pressed.

[0641] Step 2:

[0642] The terminal sends tourist destination information received from the user to the server. The transmission method uses a common internet communication protocol (e.g., HTTP POST request). The transmitted data arrives at the server in a structured format (e.g., JSON format), and upon receiving this data, the server begins the next processing step.

[0643] Step 3:

[0644] The server analyzes the received tourist destination data and initiates a process to retrieve necessary information from external APIs and databases. Specifically, it uses a map service API to obtain geographical coordinates and travel information services to retrieve information on admission fees and transportation options. The input is the user's tourist destination data, and the output is the expanded tourist destination data.

[0645] Step 4:

[0646] The server takes expanded tourist destination data as input and applies algorithms to create the optimal travel plan, taking into account travel time and distance. Here, Dijkstra's algorithm and genetic algorithms are used to calculate the shortest path. The calculation results show the order in which to visit each tourist destination and the corresponding means of transportation and time.

[0647] Step 5:

[0648] The server calculates the optimal travel plan and estimated total cost, and sends the results to the terminal. The output is formatted for user review and ready to be displayed on the terminal. The travel plan includes the order of visits to each tourist spot, estimated travel time, entrance fees at each location, and total fares.

[0649] Step 6:

[0650] The user reviews the travel plan displayed on their device and considers whether the suggested transportation and costs meet their requirements. If the user wishes to purchase tickets in advance, they select this option on their device. This action is sent back to the server as an advance purchase request. The server receives this request, processes the online ticket purchase on their behalf, and sends purchase confirmation information to the user.

[0651] (Application Example 1)

[0652] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0653] Modern travel planning involves many time-consuming steps, such as gathering information on tourist destinations, formulating optimal travel plans, and purchasing tickets in advance. Furthermore, there are limited means of obtaining detailed, real-time visual information about destinations. As a result, this can reduce the efficiency and satisfaction of travel. The problem this invention aims to solve is to address these issues while enabling travelers to have a more efficient and satisfying experience.

[0654] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0655] In this invention, the server includes means for inputting tourist destination information, means for obtaining information on entrance fees and transportation costs for each tourist destination, means for calculating the optimal route, and means for visually guiding the user through tourist destination information using augmented reality technology. This enables travelers to simultaneously enjoy efficient travel planning and real-time visual guidance.

[0656] "Means for inputting tourist destination information" refers to a mechanism that allows users to input information about tourist destinations they wish to visit into the system via a terminal.

[0657] "Means for obtaining information on admission fees and transportation costs for each tourist destination" refers to a mechanism that retrieves admission fees and transportation costs corresponding to tourist destinations entered by the user from an external database or API.

[0658] "Means for calculating the optimal route" refers to a mechanism that uses an algorithm to calculate the optimal order of visits to maximize travel efficiency, based on acquired tourist destination information and cost information.

[0659] A "means for estimating overall costs" is a mechanism that calculates the total cost of a trip based on the optimal route.

[0660] "Means for displaying the optimal route and estimated total cost to the user" refers to a mechanism that displays the calculated optimal route and total cost on the screen of the user's terminal.

[0661] "Methods for purchasing tickets to tourist destinations in advance" refers to a system that allows users to purchase admission tickets to their chosen tourist destinations online in advance.

[0662] "A means of visually guiding users with tourist destination information using augmented reality technology" refers to a mechanism that uses augmented reality (AR) technology to overlay information about tourist destinations onto real-world scenery and provide it to users.

[0663] The following describes embodiments for carrying out the invention.

[0664] This system is designed to operate by combining the user's terminal, server, and external databases and APIs. First, the user uses a smartphone or smart glasses to input information about the tourist destinations they wish to visit into the terminal. The terminal sends this information to the server. Based on the received tourist destination information, the server retrieves entrance fees and transportation costs for each destination from external databases and APIs. The server then uses this information to calculate the optimal route for visiting the destinations.

[0665] The calculations utilize distance calculations using the Geopy library and route determination techniques based on optimization algorithms. The server sends the calculated optimal route and estimated total cost to the user's device for display. At this time, augmented reality (AR) technology is used to visually guide the user with information about tourist destinations. Specifically, by overlaying information onto images of tourist destinations on the device, users can experience detailed information realistically on the spot.

[0666] Furthermore, if the user agrees, the server can purchase entrance tickets to tourist attractions online in advance. This simplifies procedures during travel and ensures a stress-free travel experience.

[0667] For example, if a user enters that they want to visit "historical buildings, nature parks, and aquariums," the server will calculate the entrance fees, shortest routes, and travel time to these locations and suggest the optimal plan.

[0668] Using a generative AI model, prompt messages related to a tourist destination specified by the user can be generated as follows:

[0669] "This app allows users to input the tourist destinations they wish to visit (e.g., historical buildings, nature parks, aquariums), calculates and presents the optimal route, and provides real-time information about those destinations."

[0670] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0671] Step 1:

[0672] Users input information about the tourist destinations they wish to visit using a terminal. This input includes the name of the tourist destination and the desired visit date, and this data is sent to the server. The terminal allows for easy information input through its interface.

[0673] Step 2:

[0674] The server receives tourist destination information sent by users and retrieves admission fees and transportation costs for each destination. This involves using external databases and APIs to search for basic information about the tourist destinations and obtain the necessary fee data. In this step, calculations are performed to filter the retrieved data using the basic information of the tourist destination as the key.

[0675] Step 3:

[0676] The server executes a mechanism to calculate the optimal visiting route based on the acquired information. Here, the Geopy library is used to calculate the distance between each tourist spot, and the route is determined by an optimization algorithm that takes travel time into account. The input is distance data between tourist spots, and the output is the optimal visiting order.

[0677] Step 4:

[0678] The server estimates the optimal route and overall cost, and sends this information to the user's terminal. This information is displayed on the user's terminal, allowing them to visually confirm their travel plan. The display is optimized for user layout, presenting the information in an easy-to-read format.

[0679] Step 5:

[0680] If the user agrees, the server will initiate the process of purchasing admission tickets to the tourist attraction online in advance. This step involves integration with the e-commerce system, and once the user's purchase intention is confirmed, the payment process will proceed.

[0681] Step 6:

[0682] The user's device processes the data necessary to visually guide them through tourist information using augmented reality (AR) technology and displays it on the screen. Input is the optimal visiting route and tourist information, and output is the information displayed via AR. AR data is displayed in real time through the device's camera.

[0683] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0684] The system according to the present invention includes not only basic functions to support travel planning, but also a function to recognize the user's emotions and dynamically adjust the plan based on them. This system handles a series of processes from inputting information about tourist destinations to presenting travel plans and purchasing tickets in advance, and incorporates feedback from an emotion engine.

[0685] The process begins with the user entering the tourist destinations they wish to visit into the system via their device, and this information is sent to the server. Based on the information received, the server obtains information from external sources to calculate entrance fees, transportation costs, and the optimal route for each tourist destination. The server analyzes this information to create an optimal tour plan and estimate the overall cost.

[0686] The emotion engine analyzes the user's emotional state through user input and interaction. This analysis is used by the server to customize travel suggestions. For example, if the user is feeling stressed, it prioritizes relaxing destinations and suggests routes with minimal travel burden. Furthermore, if the user's emotions change, a newly optimized plan is restructured and presented.

[0687] As a concrete example, suppose a user inputs their plans to visit an art museum, a botanical garden, and a theme park into the system, and is then presented with an optimal travel plan. If the user expresses feelings of joy through their device during the trip, the emotion engine can recognize this and suggest extending the time spent at the theme park to maximize the experience. In this way, the system dynamically adjusts the plan according to the user's emotions, playing a role in improving the quality of the trip.

[0688] The following describes the processing flow.

[0689] Step 1:

[0690] The user uses a device to input information about the tourist destination they wish to visit. The device then sends this input data to the server.

[0691] Step 2:

[0692] Based on the tourist destination information received by the terminal, the server retrieves information about admission fees, locations, and opening hours for each tourist destination from external databases and APIs.

[0693] Step 3:

[0694] The server also collects data on transportation methods between tourist destinations, obtaining the cost and duration of each trip. This process includes transportation schedules and fare information.

[0695] Step 4:

[0696] The server calculates the optimal sightseeing route based on the information it collects. It considers various factors such as travel time, distance, and cost minimization to derive the most efficient route for the user.

[0697] Step 5:

[0698] The server calculates the route and total cost, sends it to the terminal, and proposes it to the user. The user then confirms it on the terminal.

[0699] Step 6:

[0700] The emotion engine analyzes the user's emotional state through their interactions. Data used includes touch patterns, input speed, and facial expression recognition.

[0701] Step 7:

[0702] The server receives the results of the emotion engine's analysis and adjusts the selection of sightseeing routes and facilities according to the user's current emotions. This adjustment provides a plan that better suits the user's preferences and current mood.

[0703] Step 8:

[0704] The user reviews the proposal, and if emotional modifications are needed, they make another request to the server from their device. The server then reconfigures the plan based on that request.

[0705] Step 9:

[0706] Upon user consent, an agent on the server pre-purchases tickets for tourist attractions online. This process involves verifying payment information and retrieving ticket information.

[0707] Step 10:

[0708] The server sends final confirmation information to the device, letting the user know that they are ready to travel. This allows the user to prepare to start their trip as planned.

[0709] (Example 2)

[0710] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0711] In modern tourism planning, traditional systems operate based on pre-set plans, making it difficult to respond immediately to users' changing emotions and preferences. Furthermore, they fail to consider user emotions in their planning, resulting in a lack of optimal travel quality.

[0712] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0713] In this invention, the server includes means for inputting tourist destination information, means for acquiring information based on the tourist destination information, and means for analyzing the user's emotional state and dynamically adjusting travel suggestions. This makes it possible to provide flexible and personalized travel plans that respond to the user's emotions.

[0714] "Tourist information" refers to data about the region or facility that travelers plan to visit, including details related to specific places, events, or activities.

[0715] A "route" refers to a travel route that outlines a series of visiting sequences to efficiently tour multiple tourist destinations.

[0716] "Emotional state" refers to the user's direct reactions and feedback to the travel plan, as well as the psychological state they experience while using the system.

[0717] "Dynamic adjustment" refers to the process of changing and optimizing travel plans and sightseeing suggestions in real time to respond immediately to user needs and preferences.

[0718] "Optimization" is a method of efficiently structuring each element of a travel plan in order to maximize user satisfaction and convenience.

[0719] The system for implementing this invention has a function to support travel planning and has the characteristic of dynamically adjusting the plan based on the user's emotional state. First, the user uses a terminal to input the tourist destinations they wish to visit. The terminal has a function to receive the user's input and send it to the server. For example, the user inputs tourist destinations such as "art museum," "botanical garden," and "theme park," and the system plans the trip based on this.

[0720] The server uses external resources such as tourism information APIs and transportation information APIs to obtain tourist destination information. Using this data, the server calculates the optimal route and overall cost. Furthermore, the server is equipped with an emotion engine that analyzes user feedback and interactions to determine the user's emotional state. The results of the emotion analysis are used to modify the tourism recommendations. For example, if the user is feeling stressed, the server can suggest tourist spots that prioritize relaxation and plans that involve less travel.

[0721] For example, if a user inputs their emotional state via a device during their trip, the server can analyze this in real time and reconstruct and present a thoughtful travel plan. This dynamic functionality allows users to enjoy a more personalized travel experience.

[0722] The following prompt is an example of using a generative AI model.

[0723] "Currently, the tourist destinations I'd like to visit are art museums, botanical gardens, and theme parks. I want to minimize stress, so please suggest a plan that involves minimal travel."

[0724] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0725] Step 1:

[0726] This step involves the user using their device to input the tourist destination they wish to visit. The user operates a device such as a smartphone or tablet, entering the name of the tourist destination, such as "art museum," "botanical garden," or "theme park," and then submitting the input. The entered data is sent from the device to the server. The output at this stage is digital data related to the user's tourist destination selection.

[0727] Step 2:

[0728] This step involves the server receiving tourist destination information sent by the user and retrieving related information. The server accesses tourist information APIs and transportation information APIs to collect data such as admission fees, opening hours, and transportation options for each tourist destination. Specifically, API requests are issued, and real-time data is retrieved. The output contains detailed information about each tourist destination.

[0729] Step 3:

[0730] This step involves the server using collected data to calculate the optimal route and the total cost of the trip. The server processes the collected information and uses algorithms to optimize the order of visits. It also provides cost estimates. The data obtained in step 2 is used as input, and the route and cost estimate are output. Specific operations include map data analysis and distance calculations.

[0731] Step 4:

[0732] This step involves the server analyzing the user's emotional state using an emotion engine. When a user inputs their emotional state via a terminal during their trip, that information is sent to the server. The server analyzes this information, identifies the user's emotional state, and outputs it. The data used for emotion analysis includes text-input comments and responses to questions. The specific operation involves emotion analysis using natural language processing techniques.

[0733] Step 5:

[0734] This step involves the server dynamically adjusting the sightseeing recommendations based on the analysis results. The server reconstructs the sightseeing plan based on the emotional information obtained in step 4, optimizing it to match the user's emotions, such as minimizing the burden of travel. The input is the user's emotional state and the route and cost data obtained in step 3, and the output is the newly adjusted sightseeing plan.

[0735] Step 6:

[0736] This step involves the server sending the final travel plan to the terminal and displaying it to the user. The terminal displays the received plan on its user interface, allowing the user to select the next action. The output of step 5 is taken as input, and the display to the user is taken as output. Specifically, the operation involves displaying the travel plan details and selection options on the screen.

[0737] (Application Example 2)

[0738] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0739] Conventional tourism planning systems are unable to dynamically adjust plans based on the user's emotional state, making it difficult to provide users with the highest level of satisfaction. Therefore, there is a need to recognize the user's emotions in real time and flexibly optimize the plan based on that.

[0740] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0741] In this invention, the server includes means for inputting tourist destination information, means for obtaining information on admission fees and transportation costs for each tourist destination based on the tourist destination information, means for calculating the optimal route, and means for analyzing the user's emotional state and adjusting the sightseeing plan. This enables dynamic adjustment of the sightseeing plan in accordance with the user's emotions.

[0742] "Tourist destination information" refers to detailed information about a tourist destination, such as its name, location, characteristics, and the activities and events offered.

[0743] An "admission fee" is a charge paid for access to a tourist attraction or facility.

[0744] "Transportation expenses" refer to the costs incurred for the means of getting to a tourist destination.

[0745] A "route" is the optimal travel path set out when visiting multiple tourist destinations.

[0746] "Total cost" refers to the sum of all entrance fees, transportation costs, and other related expenses based on the sightseeing plan.

[0747] "Means of purchasing tickets in advance" refers to methods and devices for reserving and obtaining tickets such as admission tickets to tourist attractions or transportation passes before traveling.

[0748] "Emotional state" refers to the type and intensity of emotions a user exhibits in a particular situation.

[0749] An "emotion engine" is software or an algorithm used to analyze emotions from user behavior and input data.

[0750] The system for implementing this invention consists of a terminal, a server, and an emotion engine. The terminal provides an interface for the user to input information about tourist destinations they wish to visit and transmits the input information to the server. The server receives this information and retrieves information such as entrance fees and transportation costs for each tourist destination through external databases or APIs.

[0751] The server uses this information to calculate the optimal route and overall cost. The calculated information is returned to the terminal in a visualized format and presented to the user. The emotion engine analyzes user input and interaction data obtained through the terminal to determine the user's emotional state. Based on the user's state, such as feeling stressed or happy, the server dynamically adjusts and optimizes the proposed plan.

[0752] For example, if a user inputs the museum or theme park they plan to visit, and emotional data from their trip detects a sense of exhilaration, the server can suggest extending their stay. This process is repeated in real time, ensuring the user always has the best possible experience.

[0753] Examples of prompts for a generative AI model include: "Adjust the city sightseeing plan based on the user's emotions. Choose places to visit from museums, botanical gardens, and shopping malls."

[0754] The hardware will be a smartphone, and the software will use Python and an emotion recognition library (e.g., TensorFlow). An API (e.g., TripAdvisor API) will be used to obtain tourist information.

[0755] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0756] Step 1:

[0757] The terminal provides an interface for users to input information about tourist destinations they wish to visit. This input information includes the name and category of the tourist destination and is important data based on the user's preferences. The entered tourist destination information is then transmitted from the terminal to the server.

[0758] Step 2:

[0759] Based on the received tourist destination information, the server uses an external API to retrieve information on entrance fees and transportation costs for each tourist destination. This process involves communicating with an external database, obtaining the necessary cost data, organizing the results, and passing them on to the next step.

[0760] Step 3:

[0761] The server uses the data obtained above to calculate the optimal sightseeing route. Here, it executes an algorithm to minimize the user's travel time and distance, and generates the calculated optimal route information and the total cost associated with that route.

[0762] Step 4:

[0763] The server sends the generated optimal route and estimated total cost to the user's device. The device receives this information and presents it to the user in a visualized format. The data is displayed clearly on the interface so that the user can consider what action to take next.

[0764] Step 5:

[0765] The device passes user interaction and entered emotional state data to the emotion engine. The emotion engine analyzes the user's emotional state from their facial expressions and text input and returns the determination result to the server.

[0766] Step 6:

[0767] The server adjusts the sightseeing plan as needed based on data from the emotion engine. If the user reacts positively to the presented plan, it strengthens it; if they react negatively, it flexibly suggests alternatives. The recalculated plan is then presented to the user.

[0768] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0769] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0770] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0771] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0772] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0773] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0774] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0775] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0776] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0777] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0778] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0779] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0780] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0781] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0782] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0783] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0784] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0785] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0786] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0787] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0788] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0789] The following is further disclosed regarding the embodiments described above.

[0790] (Claim 1)

[0791] A means of inputting tourist destination information,

[0792] Based on the aforementioned tourist destination information, a means for obtaining information on admission fees and transportation costs for each tourist destination,

[0793] A means for calculating the optimal route,

[0794] A means for estimating the total cost based on the aforementioned optimal route,

[0795] A means for displaying the optimal route and estimated total cost to the user,

[0796] Methods for purchasing tickets to tourist attractions in advance,

[0797] A system that includes this.

[0798] (Claim 2)

[0799] The system according to claim 1, comprising means for performing the advance purchase of the aforementioned ticket with the user's consent.

[0800] (Claim 3)

[0801] The system according to claim 1, further comprising means for minimizing travel time in calculating the optimal route.

[0802] "Example 1"

[0803] (Claim 1)

[0804] An information processing device for inputting tourist destination information,

[0805] An information processing device that acquires information on admission fees and means of transportation for each tourist destination based on the aforementioned tourist destination information,

[0806] An information processing device that analyzes collected information and calculates the optimal route considering travel distance and cost,

[0807] An information processing device that estimates the total cost based on the aforementioned optimal route,

[0808] An information processing device that displays the optimal route and estimated total cost to the user,

[0809] An information processing device for purchasing admission tickets to tourist attractions in advance,

[0810] An information processing system that includes this.

[0811] (Claim 2)

[0812] The information processing system according to claim 1, which includes an information processing device that performs the advance purchase of the admission ticket with the user's consent.

[0813] (Claim 3)

[0814] The information processing system according to claim 1, further comprising an information processing device for minimizing travel time and cost in calculating the optimal route.

[0815] "Application Example 1"

[0816] (Claim 1)

[0817] A means of inputting tourist destination information,

[0818] Based on the aforementioned tourist destination information, a means for obtaining information on admission fees and transportation costs for each tourist destination,

[0819] A means for calculating the optimal route,

[0820] A means for estimating the total cost based on the aforementioned optimal route,

[0821] A means for displaying the optimal route and estimated total cost to the user,

[0822] Methods for purchasing tickets to tourist attractions in advance,

[0823] A means of visually guiding users with tourist destination information using augmented reality technology,

[0824] A system that includes this.

[0825] (Claim 2)

[0826] The system according to claim 1, comprising means for performing the advance purchase of the aforementioned ticket with the user's consent.

[0827] (Claim 3)

[0828] The system according to claim 1, further comprising means for minimizing travel time in calculating the optimal route.

[0829] "Example 2 of combining an emotion engine"

[0830] (Claim 1)

[0831] A means of inputting tourist destination information,

[0832] Based on the aforementioned tourist destination information, a means for obtaining information on admission fees and transportation costs for each tourist destination,

[0833] A means for calculating the optimal route,

[0834] A means for estimating the total cost based on the aforementioned optimal route,

[0835] A means for displaying the optimal route and estimated total cost to the user,

[0836] Methods for purchasing tickets to tourist attractions in advance,

[0837] A means to analyze the user's emotional state and dynamically adjust tourism recommendations,

[0838] A system that includes this.

[0839] (Claim 2)

[0840] The system according to claim 1, comprising means for performing the advance purchase of the aforementioned ticket with the user's consent.

[0841] (Claim 3)

[0842] The system according to claim 1, further comprising means for minimizing travel time in calculating the optimal route.

[0843] "Application example 2 when combining with an emotional engine"

[0844] (Claim 1)

[0845] A means of inputting tourist destination information,

[0846] Based on the aforementioned tourist destination information, a means for obtaining information on admission fees and transportation costs for each tourist destination,

[0847] A means for calculating the optimal route,

[0848] A means for estimating the total cost based on the aforementioned optimal route,

[0849] A means for displaying the optimal route and estimated total cost to the user,

[0850] Methods for purchasing tickets to tourist attractions in advance,

[0851] A means to analyze the user's emotional state and adjust the travel plan accordingly.

[0852] A system that includes this.

[0853] (Claim 2)

[0854] The system according to claim 1, comprising means for performing the advance purchase of the aforementioned ticket with the user's consent.

[0855] (Claim 3)

[0856] The system according to claim 1, further comprising means for minimizing travel time in calculating the optimal route, and means for proposing a new route in response to changes in the user's emotional state. [Explanation of Symbols]

[0857] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of inputting tourist destination information, Based on the aforementioned tourist destination information, a means for obtaining information on admission fees and transportation costs for each tourist destination, A means for calculating the optimal route, A means for estimating the total cost based on the aforementioned optimal route, A means for displaying the optimal route and estimated total cost to the user, Methods for purchasing tickets to tourist attractions in advance, A means of visually guiding users with tourist destination information using augmented reality technology, A system that includes this.

2. The system according to claim 1, comprising means for performing the advance purchase of the aforementioned tickets with the user's consent.

3. The system according to claim 1, further comprising means for minimizing travel time in calculating the optimal route.

Images